Computer modeling
Computer modeling

Computer modeling

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Want to design the car of the future? Here are 8,000 designs to get you started.

MIT engineers developed the largest open-source dataset of car designs, including their aerodynamics, that could speed design of eco-friendly cars and electric vehicles.

Algorithms Artificial Intelligence Climate change Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Environment MIT Schwarzman College of Computing Plants Research School of Engineering Sustainability Urban studies and planning

Advancing urban tree monitoring with AI-powered digital twins

The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.

Algorithms Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Faculty machine learning MIT Schwarzman College of Computing Profile School of Engineering Social networks

Modeling relationships to solve complex problems efficiently

Associate Professor Julian Shun develops high-performance algorithms and frameworks for large-scale graph processing.

Artificial Intelligence Computer modeling DMSE Electrical Engineering & Computer Science (eecs) machine learning Materials science and engineering Metals Research School of Engineering

Machine learning unlocks secrets to advanced alloys

An MIT team uses computer models to measure atomic patterns in metals, essential for designing custom materials for use in aerospace, biomedicine, electronics, and more.

Artificial Intelligence Climate Climate change Computer modeling Data EAPS machine learning Natural disasters Policy Research School of Science Weather modeling

Making climate models relevant for local decision-makers

A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.

Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) machine learning Mathematics MIT Schwarzman College of Computing Physics Research School of Engineering School of Science

Scientists use generative AI to answer complex questions in physics

A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.

Algorithms Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Human-computer interaction machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

To build a better AI helper, start by modeling the irrational behavior of humans

A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.

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Using deep learning to image the Earth’s planetary boundary layer

Lincoln Laboratory researchers are using AI to get a better picture of the atmospheric layer closest to Earth’s surface. Their techniques could improve weather and drought prediction.

Algorithms Artificial Intelligence Climate Climate change Computer modeling Defense Advanced Research Projects Agency (DARPA) Disaster response Earth and atmospheric sciences Environment Fluid dynamics Hurricanes machine learning Mechanical engineering Natural disasters Planetary science Research School of Engineering Weather

MIT-derived algorithm helps forecast the frequency of extreme weather

The new approach “nudges” existing climate simulations closer to future reality.